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ORCIDTimothy G. Rogers
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2020 – today
- 2024
[i3]Fangjia Shen, Timothy G. Rogers:
A Hardware Ray Tracer Datapath with Generalized Features. CoRR abs/2409.06000 (2024)- 2023
- [c24]Aaron Barnes, Fangjia Shen
, Timothy G. Rogers:
Mitigating GPU Core Partitioning Performance Effects. HPCA 2023: 530-542 - 2022
- [c23]Ahmad Alawneh, Mahmoud Khairy, Timothy G. Rogers:
A SIMT Analyzer for Multi-Threaded CPU Applications. ISPASS 2022: 248-250 - [c22]Mahmoud Khairy, Ahmad Alawneh, Aaron Barnes, Timothy G. Rogers:
SIMR: Single Instruction Multiple Request Processing for Energy-Efficient Data Center Microservices. MICRO 2022: 441-463 - 2021
- [c21]Mengchi Zhang, Ahmad Alawneh, Timothy G. Rogers:
Judging a type by its pointer: optimizing GPU virtual functions. ASPLOS 2021: 241-254 - [c20]Tsung Tai Yeh, Matthew D. Sinclair, Bradford M. Beckmann, Timothy G. Rogers:
Deadline-Aware Offloading for High-Throughput Accelerators. HPCA 2021: 479-492 - [c19]Mengchi Zhang, Ahmad Alawneh, Timothy G. Rogers:
Characterizing Massively Parallel Polymorphism. ISPASS 2021: 205-216 - [c18]Cesar Avalos Baddouh, Mahmoud Khairy, Roland N. Green, Mathias Payer, Timothy G. Rogers:
Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads. MICRO 2021: 724-737 - [c17]Vijay Kandiah, Scott Peverelle, Mahmoud Khairy, Junrui Pan, Amogh Manjunath, Timothy G. Rogers, Tor M. Aamodt, Nikos Hardavellas:
AccelWattch: A Power Modeling Framework for Modern GPUs. MICRO 2021: 738-753 - 2020
- [c16]Tsung Tai Yeh, Roland N. Green, Timothy G. Rogers:
Dimensionality-Aware Redundant SIMT Instruction Elimination. ASPLOS 2020: 1327-1340 - [c15]Mahmoud Khairy, Zhesheng Shen, Tor M. Aamodt, Timothy G. Rogers:
Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling. ISCA 2020: 473-486 - [c14]Yuan-Hsi Chou, Christopher Ng, Shaylin Cattell, Jeremy Intan, Matthew D. Sinclair, Joseph Devietti, Timothy G. Rogers, Tor M. Aamodt:
Deterministic Atomic Buffering. MICRO 2020: 981-995 - [c13]Mahmoud Khairy, Vadim Nikiforov, David W. Nellans, Timothy G. Rogers:
Locality-Centric Data and Threadblock Management for Massive GPUs. MICRO 2020: 1022-1036
2010 – 2019
- 2019
- [j4]Tsung Tai Yeh, Amit Sabne, Putt Sakdhnagool, Rudolf Eigenmann, Timothy G. Rogers:
Pagoda: A GPU Runtime System for Narrow Tasks. ACM Trans. Parallel Comput. 6(4): 21:1-21:23 (2019) - [c12]Mengchi Zhang, Roland N. Green, Timothy G. Rogers:
POSTER: Quantifying the Direct Overhead of Virtual Function Calls on Massively Parallel Architectures. PACT 2019: 497-498 - [c11]Mahmoud Khairy, Akshay Jain, Tor M. Aamodt, Timothy G. Rogers:
A Detailed Model for Contemporary GPU Memory Systems. ISPASS 2019: 141-142 - [c10]Jonathan S. Lew, Deval A. Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth Sandhupatla, Christopher Ng, Negar Goli, Matthew D. Sinclair, Timothy G. Rogers, Tor M. Aamodt:
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator. ISPASS 2019: 151-152 - 2018
- [b1]Tor M. Aamodt, Wilson Wai Lun Fung, Timothy G. Rogers:
General-Purpose Graphics Processor Architectures. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2018, ISBN 978-3-031-00631-9 - [j3]Akshay Jain, Mahmoud Khairy, Timothy G. Rogers:
A Quantitative Evaluation of Contemporary GPU Simulation Methodology. Proc. ACM Meas. Anal. Comput. Syst. 2(2): 35:1-35:28 (2018) - [c9]Anthony Gutierrez, Bradford M. Beckmann, Alexandru Dutu, Joseph Gross, Michael LeBeane, John Kalamatianos, Onur Kayiran, Matthew Poremba, Brandon Potter, Sooraj Puthoor, Matthew D. Sinclair, Mark Wyse, Jieming Yin, Xianwei Zhang, Akshay Jain, Timothy G. Rogers:
Lost in Abstraction: Pitfalls of Analyzing GPUs at the Intermediate Language Level. HPCA 2018: 608-619 - [c8]Mengchi Zhang, Roland N. Green, Timothy G. Rogers:
Characterizing the Runtime Effects of Object-Oriented Workloads on GPUs. ISPASS 2018: 109-110 - [c7]Akshay Jain, Mahmoud Khairy, Timothy G. Rogers:
A Quantitative Evaluation of Contemporary GPU Simulation Methodology. SIGMETRICS (Abstracts) 2018: 103-105 - [i2]Mahmoud Khairy, Akshay Jain, Tor M. Aamodt, Timothy G. Rogers:
Exploring Modern GPU Memory System Design Challenges through Accurate Modeling. CoRR abs/1810.07269 (2018) - [i1]Jonathan S. Lew, Deval Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth Sandhupatla, Christopher Ng, Negar Goli, Matthew D. Sinclair, Timothy G. Rogers, Tor M. Aamodt:
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator. CoRR abs/1811.08933 (2018) - 2017
- [c6]Tsung Tai Yeh, Amit Sabne, Putt Sakdhnagool, Rudolf Eigenmann, Timothy G. Rogers:
Pagoda: Fine-Grained GPU Resource Virtualization for Narrow Tasks. PPoPP 2017: 221-234 - 2016
- [c5]Tsung Tai Yeh, Amit Sabne, Putt Sakdhnagool, Rudolf Eigenmann, Timothy G. Rogers:
POSTER: Pagoda: A Runtime System to Maximize GPU Utilization in Data Parallel Tasks with Limited Parallelism. PACT 2016: 449-450 - 2015
- [c4]Timothy G. Rogers, Daniel R. Johnson, Mike O'Connor, Stephen W. Keckler:
A variable warp size architecture. ISCA 2015: 489-501 - 2014
- [j2]Timothy G. Rogers, Mike O'Connor, Tor M. Aamodt:
Learning your limit: managing massively multithreaded caches through scheduling. Commun. ACM 57(12): 91-98 (2014) - 2013
- [j1]Timothy G. Rogers, Mike O'Connor, Tor M. Aamodt:
Cache-Conscious Thread Scheduling for Massively Multithreaded Processors. IEEE Micro 33(3): 78-85 (2013) - [c3]Timothy G. Rogers, Mike O'Connor, Tor M. Aamodt:
Divergence-aware warp scheduling. MICRO 2013: 99-110 - 2012
- [c2]Tayler H. Hetherington, Timothy G. Rogers, Lisa Hsu, Mike O'Connor, Tor M. Aamodt:
Characterizing and evaluating a key-value store application on heterogeneous CPU-GPU systems. ISPASS 2012: 88-98 - [c1]Timothy G. Rogers, Mike O'Connor, Tor M. Aamodt:
Cache-Conscious Wavefront Scheduling. MICRO 2012: 72-83
Coauthor Index
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